Compared to previous generations, Millennials seem to have some very different habits that have taken both established companies and small businesses by surprise. One of these is that Generation Y doesn't seem to enjoy purchasing things.

The Atlantic's article "Why Don't Young Americans Buy Cars?" mused recently about Millennials' tendency to not care about owning a vehicle. The subtitle: "Is this a generational shift, or just a lousy economy at work?"

What if it's not an "age thing" at all? What's really causing this strange new behavior (or rather, lack of behavior)? Generational segments have profound impacts on perception and behavior, but an "ownership shift" isn't isolated within the Millennial camp. A writer for USA Today shows that all ages are in on this trend, but instead of an age group, he blames the change on the cloud, the heavenly home our entertainment goes to when current media models die. As all forms of media make their journey into a digital, de-corporeal space, research shows that people are beginning to actually prefer this disconnected reality to owning a physical product.

Antony van Leeuwenhoek wrote to the Royal Society of London in a letter dated September 17, 1683, describing “very little animalcules, very prettily a-moving,” which he had seen under a microscope in plaque scraped from his teeth. For more than three centuries after van Leeuwenhoek's observation, the human “microbiome”—the 100 trillion or so microbes that live in various nooks and crannies of the human body—remained largely unstudied, mainly because it is not so easy to extract and culture them in a laboratory. A decade ago the advent of sequencing technologies finally opened up this microbiological frontier. The Human Microbiome Project reference database, established in 2012, revealed in unprecedented detail the diverse microbial community that inhabits our bodies.

A key property of modern cities is increasing returns to scale—the finding that many socioeconomic outputs increase more rapidly than their population size. Recent theoretical work proposes that this phenomenon is the result of general network effects typical of human social networks embedded in space and, thus, is not necessarily limited to modern settlements. We examine the extent to which increasing returns are apparent in archaeological settlement data from the pre-Hispanic Basin of Mexico. We review previous work on the quantitative relationship between population size and average settled area in this society and then present a general analysis of their patterns of monument construction and house sizes. Estimated scaling parameter values and residual statistics support the hypothesis that increasing returns to scale characterized various forms of socioeconomic production available in the archaeological record and are found to be consistent with key expectations from settlement scaling theory. As a consequence, these results provide evidence that the essential processes that lead to increasing returns in contemporary cities may have characterized human settlements throughout history, and demonstrate that increasing returns do not require modern forms of political or economic organization.

For an artificial agent to be considered truly intelligent it needs to excel at a variety of tasks considered challenging for humans. To date, it has only been possible to create individual algorithms able to master a single discipline — for example, IBM's Deep Blue beat the human world champion at chess but was not able to do anything else. Now a team working at Google's DeepMind subsidiary has developed an artificial agent — dubbed a deep Q-network — that learns to play 49 classic Atari 2600 'arcade' games directly from sensory experience, achieving performance on a par with that of an expert human player. By combining reinforcement learning (selecting actions that maximize reward — in this case the game score) with deep learning (multilayered feature extraction from high-dimensional data — in this case the pixels), the game-playing agent takes artificial intelligence a step nearer the goal of systems capable of learning a diversity of challenging tasks from scratch.

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita . This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method— the selective predictability scheme —in which we adopt a strategy similar to the methods of analogues , firstly introduced by Lorenz, to assess future evolution of countries.

For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network

Indirect reciprocity means that my behavior towards you also depends on what you have done to others. Indirect reciprocity is associated with the evolution of social intelligence and human language. Most approaches to indirect reciprocity assume obligatory interactions, but here we explore optional interactions.

The question What is Complexity? has occupied a great deal of time and paper over the last 20 or so years. There are a myriad different perspectives and definitions but still no consensus. In this paper I take a phenomenological approach, identifying several factors that discriminate well between systems that would be consensually agreed to be simple versus others that would be consensually agreed to be complex - biological systems and human languages. I argue that a crucial component is that of structural building block hierarchies that, in the case of complex systems, correspond also to a functional hierarchy. I argue that complexity is an emergent property of this structural/functional hierarchy, induced by a property - fitness in the case of biological systems and meaning in the case of languages - that links the elements of this hierarchy across multiple scales. Additionally, I argue that non-complex systems "are" while complex systems "do" so that the latter, in distinction to physical systems, must be described not only in a space of states but also in a space of update rules (strategies) which we do not know how to specify. Further, the existence of structural/functional building block hierarchies allows for the functional specialisation of structural modules as amply observed in nature. Finally, we argue that there is at least one measuring apparatus capable of measuring complexity as characterised in the paper - the human brain itself.

We inspect a possible clustering structure of the corruption perception among 134 countries. Using the average linkage clustering, we uncover a well-defined hierarchy in the relationships among countries. Four main clusters are identified and they suggest that countries worldwide can be quite well separated according to their perception of corruption. Moreover, we find a strong connection between corruption levels and a stage of development inside the clusters. The ranking of countries according to their corruption perfectly copies the ranking according to the economic performance measured by the gross domestic product per capita of the member states. To the best of our knowledge, this study is the first one to present an application of hierarchical and clustering methods to the specific case of corruption.

In the nearly 70 years since the first modern digital computer was built, the above specs have become all but synonymous with computing. But they need not be. A computer is defined not by a particular set of hardware, but by being able to take information as input; to change, or “process,” the information in some controllable way; and to deliver new information as output. This information and the hardware that processes it can take an almost endless variety of physical forms. Over nearly two centuries, scientists and engineers have experimented with designs that use mechanical gears, chemical reactions, fluid flows, light, DNA, living cells, and synthetic cells.

Although the original vision for artificial intelligence was the simulation of (implicitly human) intelligence, research has gradually shifted to autonomous systems that compete with people. The resultant popular attitude toward artificial intelligence, we argue here, is by turns disdain, grudging acceptance, and fear. That attitude not only limits our work's potential, but also imperils its support. This paper proposes a constructive alternative: the development of collaborative intelligence. As envisioned here, a collaborative intelligence does not require encyclopedic command and need not be limited to a single problem. The necessary components of a collaborative intelligence are nearly at hand, and the key issues readily identified. As a first step, this paper proposes three challenging but accessible problems that would both change the public perception of artificial intelligence and spur substantive research to advance our science.

The lipid bilayer membrane, which is the foundation of life on Earth, is not viable outside of biology based on liquid water. This fact has caused astronomers who seek conditions suitable for life to search for exoplanets within the “habitable zone,” the narrow band in which liquid water can exist. However, can cell membranes be created and function at temperatures far below those at which water is a liquid? We take a step toward answering this question by proposing a new type of membrane, composed of small organic nitrogen compounds, that is capable of forming and functioning in liquid methane at cryogenic temperatures. Using molecular simulations, we demonstrate that these membranes in cryogenic solvent have an elasticity equal to that of lipid bilayers in water at room temperature. As a proof of concept, we also demonstrate that stable cryogenic membranes could arise from compounds observed in the atmosphere of Saturn’s moon, Titan, known for the existence of seas of liquid methane on its surface.

For over half a century, the biological roles of nucleic acids as catalytic enzymes, intracellular regulatory molecules, and the carriers of genetic information have been studied extensively. More recently, the sequence-specific binding properties of DNA have been exploited to direct the assembly of materials at the nanoscale. Integral to any methodology focused on assembling matter from smaller pieces is the idea that final structures have well-defined spacings, orientations, and stereo-relationships. This requirement can be met by using DNA-based constructs that present oriented nanoscale bonding elements from rigid core units. Here, we draw analogy between such building blocks and the familiar chemical concepts of “bonds” and “valency” and review two distinct but related strategies that have used this design principle in constructing new configurations of matter.

A great deal of research to inform environmental conservation and management takes a predict-and-prescribe strategy in which improving forecasts about future states of ecosystems is the primary goal. But sufficiently thorough understanding of ecosystems needed to reduce deep uncertainties is probably not achievable, seriously limiting the potential effectiveness of the predict-and-prescribe approach. Instead, research should integrate more closely with policy development to identify the range of alternative plausible futures and develop strategies that are robust across these scenarios and responsive to unpredictable ecosystem dynamics.

Corruption is one of the most serious obstacles for ecosystem management and biodiversity conservation. In particular, more than half of the loss of forested area in many tropical countries is due to illegal logging, with corruption implicated in a lack of enforcement. Here we study an evolutionary game model to analyze the illegal harvesting of forest trees, coupled with the corruption of rule enforcers.

Economic games such as the public goods game are increasingly being used to measure social behaviours in humans and non-human primates. The results of such games have been used to argue that people are pro-social, and that humans are uniquely altruistic, willingly sacrificing their own welfare in order to benefit others. However, an alternative explanation for the empirical observations is that individuals are mistaken, but learn, during the game, how to improve their personal payoff.

Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper.

We are naturally constrained by many natural laws in our universe. Our governments are likewise constrained by physical laws of nature as well as the natural laws behind people, societies, economies, and ecosystems. Where the constraints came from in nature, I don't know. But what I do see, is that like the natural laws of the universe, societies impose other constraints upon our actions, behaviors, perceptions, chosen courses of action, abilities to frame issues and topics, abilities to define conditions within our social systems. Governments can likewise make and define constraints for behaviors or willingness and ability to behave on the part of the citizenry, either by offering incentives to get people to behave in a particular way or to penalize and possibly limit some actions and chosen patterns of behavior.

It should be noted that the laws and chosen constraints and incentives of the government on this level of existence can only be as good as the people who sit within them and make choices. They are also limited by the physical laws of the universe and the natural laws, conditions, desires, and motives of the general public that composes the whole of society in aggregate and as that which is greater than the aggregate; the combined whole of human thought, behavior, and sentiment.

These human-made constraints (created by governments and social authority figures) are also imperfect in their ability to contain and constrain the society, since the society and its members have autonomy from the government. Humans and human societies are more constrained by the natural laws and the limitations of knowledge and perception that are present in our brains and neural systems. Therefore, it can be said that human-made social constraints are less important than the natural ones that exist amongst ourselves and within the universe that we are apart of.

Therefore, I think that in order to continue to advance humanity and contribute to our potential to survive, endure, and thrive, we should be constantly and safely pushing at the constraints of what we already know and can do as individuals and as a species. Our government(s) should focus on studying the universal natural laws of societies, economies, human behavior, and environmental functions in addition to the particular laws of their own societies, making laws and legal systems that work better and better with the natural laws of their own societies and amongst all human societies. We should capitalize on our differences of perspective and opinion, sifting out those that don't fall into line with discovered reality while using that which is accurate to complete the puzzles of our universe in order to produce something greater than what we've presently got and to continue to advance ourselves safely and in accordance with what is actually helpful, healthful, and ethical for all sentient life in the universe. Study, research, observation, and exploration are what will make tomorrow better than today, even as the natural laws and some conditions remain the same. Health, well-being, quality of life, sustainability, and the ability to thrive for all are what we need to prioritize and produce as a society over financial profits and short term economic gains for a few. Some constraints can be pushed, some can't, and some really shouldn't from the perspective of health, well-being, quality of life, and the ability to thrive for all. Welcome to nature.

From glorious rainbows to the intricate mechanics of the human eye, light lies at the heart of phenomena that have fascinated scientists for millennia. Today, the latest optical technologies — from lasers to solar cells — harness light to advance physics and to serve society's needs.

To put light itself in the spotlight, the United Nations designated 2015 the International Year of Light and Light-based Technologies. The celebration is also pegged to a string of anniversaries: Augustin-Jean Fresnel's proposal in 1815 that light is a wave; James Clerk Maxwell's 1865 electromagnetic theory; Albert Einstein's 1915 general theory of relativity; and in 1965, discovery of the cosmic microwave background (CMB) radiation and the development of optical fibres for communication.

The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.

Metasystem transitions are events representing the evolutionary emergence of a higher level of organization through the integration of subsystems into a higher “metasystem” (A1+A2+A3=B). Such events have occurred several times throughout the history of life (e.g., emergence of life, multicellular life, sexual reproduction). The emergence of new levels of organization has occurred within the human system three times, and has resulted in three broadly defined levels of higher control, producing three broadly defined levels of group selection (e.g., band/tribe, chiefdom/kingdom, nation-state/international). These are “Human Metasystem Transitions” (HMST). Throughout these HMST several common system-level patterns have manifested that are fundamental to understanding the nature and evolution of the human system, as well as our potential future development. First, HMST have been built around the control of three mostly distinct primary energy sources (e.g., hunting, agriculture, industry). Second, the control of new energy sources has always been achieved and stabilized by utilizing the evolutionary emergence of a more powerful information-processing medium (e.g., language, writing, printing press). Third, new controls emerge with the capability of organizing energy flows over larger expanses of space in shorter durations of time: bands/tribes controlled regional space and stabilized for hundreds of thousand of years, chiefdoms/kingdoms controlled semi-continental expanses of space and stabilized for thousands of years, and nation-states control continental expanses of space and have stabilized for centuries. This space-time component of hierarchical metasystem emergence can be conceptualized as the active compression of space-time-energy-matter (STEM compression) enabled by higher informational and energetic properties within the human system, which allow for more complex organization (i.e., higher subsystem integration). In this framework, increased information-energy control and feedback, and the consequent metasystem compression of space-time, represent the theoretical pillars of HMST theory. Most importantly, HMST theory may have practical application in modeling the future of the human system and the nature of the next human metasystem.

Zipf's law is just one out of many universal laws proposed to describe statistical regularities in language. Here we review and critically discuss how these laws can be statistically interpreted, fitted, and tested (falsified). The modern availability of large databases of written text allows for tests with an unprecedent statistical accuracy and also a characterization of the fluctuations around the typical behavior. We find that fluctuations are usually much larger than expected based on simplifying statistical assumptions (e.g., independence and lack of correlations between observations).These simplifications appear also in usual statistical tests so that the large fluctuations can be erroneously interpreted as a falsification of the law. Instead, here we argue that linguistic laws are only meaningful (falsifiable) if accompanied by a model for which the fluctuations can be computed (e.g., a generative model of the text). The large fluctuations we report show that the constraints imposed by linguistic laws on the creativity process of text generation are not as tight as one could expect.

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